The aim of this project is to continue to invent, refine and apply generalizable computational tools for neutron protein crystallography. Our primary focus will be to provide innovative, but practical solutions, that can be rapidly deployed to the target user community to address the computational bottleneck in neutron protein crystallography and to determine the neutron structures of a series of proteins, many with high biomedical importance, that span a spectrum of size and complexity. We will continue our current work adapting these computational tools for incorporation into PHENIX (Python-based Hierarchical Environment for Integrated Xtallography) for automated crystallography as extensible C++ and Python modules. The software will use and contribute towards the basic programming tools for crystallography in the Computational Crystallographic Toolbox (cctbx). Our vision is to contribute to a computational workbench that structural biologist, with a range of crystallographic experience, can use alternately for neutron, X-ray, or global neutron/X-ray/energy crystallography. The computational tools will integrate all tasks required for handling neutron intensity data scaling, wavelength normalization, attenuation correction and handling, determination and computation of phases, map generation and innovative solutions to multiple map representation, automated map interpretation, model building and refinement into one system. Automatic decision-making concepts will minimize human interventions and decrease time needed to refine structures. Our software developments will also be generalizable to X-ray crystallography. These tools will allow structure determination, model building, and refinement against any combination of neutron, X-ray and energy minimization functions. Structural biologists will use the same system in an interoperable way for structure determination and refinement based on X-ray, neutron and energetic data. PUBLIC HEALTH RELEVANCE: Neutron crystallography is a technique that provides unique types of information on the enzymatic function and drug binding properties of biological macromolecules that are highly relevant to public health. The aim of this project is to continue to invent, refine and apply generalizable computational tools that can be applied to address the computational bottlenecks in neutron protein crystallography and then to use those tools to study a series of proteins of high biomedical importance that span a spectrum of size and complexity.